Overdrive: Making SPDZ Great Again

By Marcel Keller, Valerio Pastro, Dragos Rotaru. 2018

355 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications

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Citations in the corpus

Secure Evaluation of Quantized Neural Networks (2019, neutral): “See Keller et al. [41] for details.”
Blind Justice: Fairness with Encrypted Sensitive Attributes (2018, background): “In this setting, several protocols for triple generation (which we did not describe) are available (Keller et al., 2018), and under continuous improvement.”
Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning (2019, background): “This paradigm has proved its ability to improve the efficiency of protocols in both theoretical [28]–[33] and practical [4], [34]–[41] domains.”
SPD Z 2 k : Eﬃcient MPC mod 2 k for Dishonest Majority (2018, neutral): “In very recent work [15], Keller, Pastro and Rotaru presented a new variant of the SPDZ protocol that improves upon the performance of MASCOT.”
New Primitives for Actively-Secure MPC over Rings with Applications to Private Machine Learning (2019, methodology): “Besides containing an implementation of MASCOT, Bristol-SPDZ also implements the most efﬁ-cient SPDZ preprocessing protocol, Overdrive [24], making the combination of FRESCO and Bristol-SPDZ a sensible choice for doing a fair comparison of both SPD Z 2 k and SPDZ, from preprocessing to online…”
Secure and Efficient Federated Transfer Learning (2019, methodology): “The offline phase of the protocol is based on LowGear version of Overdrive [17], which is the most efficient preprocessing protocol for two parties.”
MP-SPDZ: A Versatile Framework for Multi-Party Computation (2020, methodology): “[12]) and therefore does not scale as well with the number of parties as HighGear.”
Generalizing the SPDZ Compiler For Other Protocols (2018, methodology): “For the latter, this has been done in various previous works [13, 20].”
Efficient Multi-Key Homomorphic Encryption with Packed Ciphertexts with Application to Oblivious Neural Network Inference (2019, background): “Recent years witnessed a large body of works on improving the practical efficiency of MPC, and state-of-the-art protocols have achieved orders of magnitude improvements on performance (see e.g. [20, 36, 49]).”
ABY2.0: Improved Mixed-Protocol Secure Two-Party Computation (2020, methodology): “Later, works like [59, 60, 79] focused on improving the setup cost using techniques like Oblivious Transfer (OT) and Homomorphic Encryption (HE).”
SPDℤ2k: Efficient MPC mod 2k for Dishonest Majority (2018, positive): “In very recent work [15], Keller, Pastro and Rotaru presented a new variant of the SPDZ protocol that improves upon the performance of MASCOT.”
Secure Computation for Machine Learning With SPDZ (2019, methodology): “We selected the SPDZ [1, 6, 7] framework for our experiments since it is one of the main and most comprehensive implementations for multiparty computation protocols, which provide malicious security and support more than two parties.”
Adding Distributed Decryption and Key Generation to a Ring-LWE Based CCA Encryption Scheme (2019, methodology): “The same technique is used in the High Gear variant of the Overdrive [18] offline phase for SPDZ.”
Use your Brain! Arithmetic 3PC For Any Modulus with Active Security (2019, background): “Overdrive [KPR18] does preprocessing with additively homomorphic encryption and proofs of knowledge.”